Maintenance is regularly performed on aircraft to replace aged aircraft parts with replacement aircraft parts to keep the aircraft in a safe condition for in-service operation. Thus, it is desired to predict the demand for the replacement aircraft parts for maintenance during an in-service lifecycle of the aircraft. However, predicting the demand for the replacement aircraft parts is challenging. The relatively small amount of available historic data on aircraft part replacement (especially for a new model of aircraft) creates one challenge for predicting the demand for replacement aircraft parts. Also, many aged aircraft parts removed from aircraft that have been retired from service are reconditioned and sold as replacement aircraft parts. This adds to the overall pool of available replacement aircraft parts, which reduces the demand for new replacement aircraft parts. The above factors create a nondeterministic environment for predicting the demand for the replacement aircraft parts. Thus, conventional methods of using statistical models may not be effective in predicting the demand for the replacement aircraft parts.
Therefore it would be desirable to have a system and method that take into account at least some of the issues discussed above, as well as other possible issues.